Cenci, Simone;
Kealhofer, Stephen;
(2022)
A causal approach to test empirical capital structure regularities.
Journal of Finance and Data Science
, 8
pp. 214-232.
10.1016/j.jfds.2022.09.002.
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Abstract
Capital structure theories are often formulated as causal narratives to explain which factors drive financing choices. These narratives are usually examined by estimating cross–sectional relations between leverage and its determinants. However, the limitations of causal inference from observational data are often overlooked. To address this issue, we use structural causal modeling to identify how classic determinants of leverage are causally linked to capital structure and how this causal structure influences the effect-estimation process. The results provide support for the causal role of variables that measure the potential for information asymmetry concerning firms’ market values. Overall, our work provide a crucial step to connect capital structure theories with their empirical tests beyond simple correlations.
Type: | Article |
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Title: | A causal approach to test empirical capital structure regularities |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.jfds.2022.09.002 |
Publisher version: | https://doi.org/10.1016/j.jfds.2022.09.002 |
Language: | English |
Additional information: | © The Author(s), 2022. This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CC-BY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Keywords: | Causal inference, Structural causal models, Capital structure |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10196466 |
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